Yesterday the hearing in the DOJ’s challenge to stop the Aetna-Humana merger got underway, and last week phase 1 of the Cigna-Anthem merger trial came to a close.

The DOJ’s challenge in both cases is fundamentally rooted in a timeworn structural analysis: More consolidation in the market (where “the market” is a hotly-contested issue, of course) means less competition and higher premiums for consumers.

Following the traditional structural playbook, the DOJ argues that the Aetna-Humana merger (to pick one) would result in presumptively anticompetitive levels of concentration, and that neither new entry not divestiture would suffice to introduce sufficient competition. It does not (in its pretrial brief, at least) consider other market dynamics (including especially the complex and evolving regulatory environment) that would constrain the firm’s ability to charge supracompetitive prices.

Aetna & Humana, for their part, contend that things are a bit more complicated than the government suggests, that the government defines the relevant market incorrectly, and that

the evidence will show that there is no correlation between the number of [Medicare Advantage organizations] in a county (or their shares) and Medicare Advantage pricing—a fundamental fact that the Government’s theories of harm cannot overcome.

The trial will, of course, feature expert economic evidence from both sides. But until we see that evidence, or read the inevitable papers derived from it, we are stuck evaluating the basic outlines of the economic arguments based on the existing literature.

This white paper counsels extreme caution in the use of past statistical studies of the purported effects of health insurance company mergers to infer that today’s proposed mergers—between Aetna/Humana and Anthem/Cigna—will likely have similar effects. Focusing on one influential study—Paying a Premium on Your Premium…—as a jumping off point, we highlight some of the many reasons that past is not prologue.

In short: extrapolated, long-term, cumulative, average effects drawn from 17-year-old data may grab headlines, but they really don’t tell us much of anything about the likely effects of a particular merger today, or about the effects of increased concentration in any particular product or geographic market.

By way of reference, Dafny, et al. found average premium price increases from the 1999 Aetna/Prudential merger of only 0.25 percent per year for two years following the merger in the geographic markets they studied. “Health Insurance Mergers May Lead to 0.25 Percent Price Increases!” isn’t quite as compelling a claim as what critics have been saying, but it’s arguably more accurate (and more relevant) than the 7 percent price increase purportedly based on the paper that merger critics like to throw around.

Moreover, different markets and a changed regulatory environment alone aren’t the only things suggesting that past is not prologue. When we delve into the paper more closely we find even more significant limitations on the paper’s support for the claims made in its name, and its relevance to the current proposed mergers.